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付义强,张正旺,陈本平,凌征文.2011.四川老君山自然保护区红翅噪鹛冬季栖息地特征.动物学杂志,46(5):48-54.
四川老君山自然保护区红翅噪鹛冬季栖息地特征
Winter Habitat Characteristics of Red-winged Laughingthrush at Laojunshan National Nature Reserve in China
投稿时间:2011-03-10  修订日期:2011-05-09
DOI:
中文关键词:  红翅噪鹛  栖息地  冬季  Logistic回归分析  老君山自然保护区
英文关键词:Red-winged Laughingthrush (Garrulax formosus)  Habitat  Winter  Logistic regression  Laojunshan Nature Reserve
基金项目:
作者单位E-mail
付义强 北京师范大学生物多样性与生态工程教育部重点实验室 生命科学学院 北京 100875
乐山师范学院化学与生命科学学院 四川 乐山 614004 
 
张正旺 北京师范大学生物多样性与生态工程教育部重点实验室 生命科学学院 北京 100875 zzw@bnu.edu.cn 
陈本平 四川老君山国家级自然保护区 四川 屏山 645350  
凌征文 四川老君山国家级自然保护区 四川 屏山 645350  
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中文摘要:
      2010年1月和2011年1月,在四川老君山国家级自然保护区对红翅噪鹛(Garrulax formosus)的冬季栖息地特征进行了初步研究。在研究区内,红翅噪鹛冬季多集小群活动,主要选择次生林,而回避原生林和人工林。2个冬季在野外共遇见红翅噪鹛21群78只。通过比较分析,发现红翅噪鹛喜欢在海拔较低、坡位较高、坡向偏阳、乔木稀疏矮小、灌木稠密、草本植物较高、藤本植物较丰富及植被总盖度较大的区域活动。此外,红翅噪鹛还倾向于选择距离林缘和水源较近的生境。Logistic回归分析的结果表明:坡向、乔木均高和灌木盖度是影响红翅噪鹛冬季栖息地选择的3个最重要变量,由这3个变量组成的回归模型为:π(x)=eg(x)/(1+eg(x)),g(x)=-1.927+1.824×坡向-0.337×乔木均高+2.136×灌木盖度。该模型对红翅噪鹛冬季栖息地选择的预测准确性达到81.7%。
英文摘要:
      Studies on winter habitat characteristics of Red-winged Laughingthrush (Garrulax formosus) were conducted at Laojunshan National Nature Reserve in Sichuan Province, China in January of 2010 and 2011.Red-winged Laughingthrushes often made in small flocks in winter, total of 78 individuals in 21 flocks were recorded in the study area during study period. They preferred secondary forest, and avoided primary forest and artificial forest. The results of comparative analysis indicated that Red-winged Laughingthrushes used the habitats with less and lower trees, dense shrubs, higher herbs, abundant lianes and larger canopy of vegetation at upper part of slope, in southward slope aspect, in lower altitude. In addition, Red-winged Laughingthrushes also preferred to select the sites close to the forest edge and water resources. Logistic regression analyse suggested that slope aspect, average height of trees and cover of shrubs were the most important three factors influencing the habitat selection of Red-winged Laughingthrush. The regression model could be formally expressed as: π(x)=eg(x)/(1 + eg(x)), g(x)=-1.927 + 1.824 × slope aspect-0.337 × average height of trees + 2.136 × cover of shrubs. The model could predict the occurrence of wintering habitat of Red-winged Laughingthrush with an accuracy of 81.7%.
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